Innovations in diagnosing and verifying the level of success of treatment of disease have migrated from external imaging processes to internal diagnostic processes. In particular, diagnostic equipment and processes have been developed for diagnosing vasculature blockages and other vasculature disease by means of ultra-miniature sensors placed upon the distal end of a flexible elongate member such as a catheter, or a guide wire used for catheterization procedures. For example, known medical sensing techniques include angiography, intravascular ultrasound (IVUS), forward looking IVUS (FL-IVUS), fractional flow reserve (FFR) determination, a coronary flow reserve (CFR) determination, optical coherence tomography (OCT), transesophageal echocardiography, and image-guided therapy. Each of these techniques may be better suited for different diagnostic situations. To increase the chance of successful treatment, health care facilities may have a multitude of imaging, treatment, diagnostic, and sensing modalities on hand in a catheter lab during a procedure. Traditionally, when a patient undergoes multiple procedures associated with different modalities, it may be necessary to enter identifying information about the patient for each of the different modalities. In other words, the same patient information may have to be entered multiple times. Such duplication of effort may lead to clerical errors and wasted resources. Further, inconsistencies in patient diagnosis may be caused by each modality maintaining a separate patient record for the same patient.
Additionally, data associated with each medical modality is traditionally acquired and managed by distinct hardware or software systems. As a result, a practitioner may review a data set associated with a first medical modality on a different system than a data set associated with a second, different medical modality. Transitioning between systems to review data acquired from the same patient may lead to inefficient and inaccurate diagnoses. Further, archival mechanisms and archival storage locations may be different between different modality acquisition systems. For example, a patient's IVUS data may be archived in a different location and in a different format that the same patient's OCT data, making data retrieval inefficient and burdensome.
Further, when archived medical data is used for teaching and other non-diagnostic purposes, it is typical to remove any information that may identify the patient from which the data was acquired. Traditionally, removal of identifying information before archival is done by a technician who manually deletes patient data from selected fields. Anonymizing data in such a manner is often error prone and often does not result in all identifying information being removed.
Accordingly, while the existing case management systems and methods have been generally adequate for their intended purposes, they have not been entirely satisfactory in all respects.